Worked on enhancing data consistency for the apache/paimon repository by improving the integration between Paimon and Spark. Focused on preserving batch data integrity during streaming appends, the work involved updating the PaimonSparkTableBase to support the OVERWRITE_BY_FILTER capability at the batch level. This approach ensured that batch data would not be unintentionally overwritten by streaming writes, addressing a key data engineering challenge. Regression tests were implemented to verify correctness across batch and streaming scenarios. The work was carried out using Scala and Spark, demonstrating a methodical approach to data engineering and careful attention to the nuances of batch versus streaming data workflows.